Oracle Data Miner 11g R2 – New Features
There are many new features in the new tool and these can be grouped under the following headings:
: The first step of every data mining project involves investigating the data to try to learn from the data, gather some initial information and investigate if there are any patterns in the data
: This gives the user a more intuitive way to work with the tool and with the overall process of data mining. It allows for the repeated rerunning of the data modelling process without having to input and define each step again. You had to do this in the previous version of the tool
Generate multiple models at the same time
: This is one of the major improvements in the tool. It allows you to create models using each of the algorithms available for each data mining techniques, in one step, instead of repeatedly defining each in the pervious version of the tool.
Graphical representations of models
: Another major new feature. The tool now produces Decision Trees and Clusters graphically. With the Decisions Trees we can now see on the screen how the tree looks and then to investigate the different branches of it to see how the tree was built. We can also see what rules were generated to create these branches.
Evaluation of all the developed models
: Another major new feature. In the previous version of the tool you were presented with a set of evaluation diagrams and measures for each model. You were not able to see all the results on one graph and you had to resort to having multiple windows open at the same time to try to compare the results. Now we can get the evaluation measures and graphs for all the models on the one set of graphs. This allows a data miner to concentrate on determining the most appropriate model to use.
Each of these new features really deserve a post by themselves to illustrate their new capabilities. These posts will follow over the coming weeks.